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Home / Proceedings / Proceedings of the International AAAI Conference on Web and Social Media, 11 / Vol. 11 No. 1 (2017): Eleventh International AAAI Conference on Web and Social Media

Who Makes Trends? Understanding Demographic Biases in Crowdsourced Recommendations

February 1, 2023

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Abstract:

Users of social media sites like Facebook and Twitter rely on crowdsourced content recommendation systems (for example, Trending Topics) to retrieve important and useful information. Contents selected for recommendation indirectly give the initial users who promoted (by liking or posting) the content an opportunity to propagate their messages to a wider audience. Hence, it is important to understand the demographics of people who make a content worthy of recommendation, and explore whether they are representative of the media site's overall population. In this work, using extensive data collected from Twitter, we make the first attempt to quantify and explore the demographic biases in the crowdsourced recommendations. Our analysis, focusing on the selection of trending topics, finds that a large fraction of trends are promoted by crowds whose demographics are significantly different from the overall Twitter population. More worryingly, we find that certain demographic groups are systematically under-represented among the promoters of the trending topics. To make the demographic biases in Twitter trends more transparent, we developed and deployed a Web-based service Who-Makes-Trends at twitter-app.mpi-sws.org/who-makes-trends.

Authors

Abhijnan Chakraborty,Johnnatan Messias,Fabricio Benevenuto,Saptarshi Ghosh,Niloy Ganguly,Krishna Gummadi

Indian Institute of Technology Kharagpur,Universidade Federal de Minas Gerais,Universidade Federal de Minas Gerais,Indian Institute of Technology Kharagpur,Indian Institute of Technology Kharagpur,Max Planck Institute for Software Systems


DOI:

10.1609/icwsm.v11i1.14894


Topics: ICWSM

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HOW TO CITE:

Abhijnan Chakraborty,Johnnatan Messias,Fabricio Benevenuto,Saptarshi Ghosh,Niloy Ganguly,Krishna Gummadi Who Makes Trends? Understanding Demographic Biases in Crowdsourced Recommendations (2017) 22-31.

Abhijnan Chakraborty,Johnnatan Messias,Fabricio Benevenuto,Saptarshi Ghosh,Niloy Ganguly,Krishna Gummadi Who Makes Trends? Understanding Demographic Biases in Crowdsourced Recommendations ICWSM 2017, 22-31.

Abhijnan Chakraborty,Johnnatan Messias,Fabricio Benevenuto,Saptarshi Ghosh,Niloy Ganguly,Krishna Gummadi (2017). Who Makes Trends? Understanding Demographic Biases in Crowdsourced Recommendations. , 22-31.

Abhijnan Chakraborty,Johnnatan Messias,Fabricio Benevenuto,Saptarshi Ghosh,Niloy Ganguly,Krishna Gummadi. Who Makes Trends? Understanding Demographic Biases in Crowdsourced Recommendations. 2017 p.22-31.

Abhijnan Chakraborty,Johnnatan Messias,Fabricio Benevenuto,Saptarshi Ghosh,Niloy Ganguly,Krishna Gummadi. 2017. Who Makes Trends? Understanding Demographic Biases in Crowdsourced Recommendations. "". 22-31.

Abhijnan Chakraborty,Johnnatan Messias,Fabricio Benevenuto,Saptarshi Ghosh,Niloy Ganguly,Krishna Gummadi. (2017) "Who Makes Trends? Understanding Demographic Biases in Crowdsourced Recommendations", , p.22-31

Abhijnan Chakraborty,Johnnatan Messias,Fabricio Benevenuto,Saptarshi Ghosh,Niloy Ganguly,Krishna Gummadi, "Who Makes Trends? Understanding Demographic Biases in Crowdsourced Recommendations", ICWSM, p.22-31, 2017.

Abhijnan Chakraborty,Johnnatan Messias,Fabricio Benevenuto,Saptarshi Ghosh,Niloy Ganguly,Krishna Gummadi. "Who Makes Trends? Understanding Demographic Biases in Crowdsourced Recommendations". , 2017, p.22-31.

Abhijnan Chakraborty,Johnnatan Messias,Fabricio Benevenuto,Saptarshi Ghosh,Niloy Ganguly,Krishna Gummadi. "Who Makes Trends? Understanding Demographic Biases in Crowdsourced Recommendations". , (2017): 22-31.

Abhijnan Chakraborty,Johnnatan Messias,Fabricio Benevenuto,Saptarshi Ghosh,Niloy Ganguly,Krishna Gummadi. Who Makes Trends? Understanding Demographic Biases in Crowdsourced Recommendations. ICWSM[Internet]. 2017[cited 2023]; 22-31.


ISSN: 2334-0770


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